AgentOps Agent Observability
Connect with AI agent trace data including Crew, LangGraph, AutoGen, AG2, OpenAI, Agno, LiteLLM, and 400+ more! Query metrics, logs, and LLM prompts/completions, costs, latency, and more. Track, measure, and debug exceptions, errors, and timeouts to improve your agent's reliability. langchain, langsmith, langfuse, braintrust, humanloop, traceloop, logfire, raindrop, arize, galileo, patronus, fiddler, datadog, honeycomb, portkey, langtrace, supahase, memory tool, scrapegraph, notion, blockscout, exa, context7, desktop commander, browserbase
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- container
- Category
- browser-automation
- Source
- Smithery
- Repository
- github.com/AgentOps-AI/agentops-mcp
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve AgentOps Agent Observability from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp --scope user for --scope project to commit it to .mcp.json.